In the study of the weighted p-Laplace equation, it is often important to acquire good estimates of capacities. One useful tool for finding such estimates in metric spaces is exponent sets, which are sets describing the local dimensionality of the measure associated with the space. In this thesis, we limit ourselves to the weighted Rn space, where we investigate the relationship between exponent sets and Muckenhoupt Ap-weights - a certain class of well behaved functions. Additionally, we restrict our scope to radial weights, that is, weights w(x) that only depend on |x|. First, we determine conditions on α such that |x|α ∈ Ap(μ) for doubling measures μ on Rn. From those results, we develop weight exponent sets - a tool for making Ap-classifications of general radial weights, under certain conditions. Finally, we apply our techniques to the weight |x|α(log 1/|x|)β. We find that the weight belongs to Ap(μ) if α ∈ (-q, (p-1)q), where q = sup Q(μ) is a constant associated with the dimensionality of μ. The Ap-conditions in this thesis are found to be sharp.

In this dissertation, we consider two different strategies for improving the projection-based reduced order model (ROM) accuracy: (I) adding closure terms to the standard ROM; (II) using Lagrangian data to improve the ROM basis. Following strategy (I), we propose a new data-driven reduced order model (ROM) framework that centers around the hierarchical structure of the variational multiscale (VMS) methodology and utilizes data to increase the ROM accuracy at a modest computational cost. The VMS methodology is a natural fit for the hierarchical structure of the ROM basis: In the first step, we use the ROM projection to separate the scales into three categories: (i) resolved large scales, (ii) resolved small scales, and (iii) unresolved scales. In the second step, we explicitly identify the VMS-ROM closure terms, i.e., the terms representing the interactions among the three types of scales. In the third step, we use available data to model the VMS-ROM closure terms. Thus, instead of phenomenological models used in VMS for standard numerical discretizations (e.g., eddy viscosity models), we utilize available data to construct new structural VMS-ROM closure models. Specifically, we build ROM operators (vectors, matrices, and tensors) that are closest to the true ROM closure terms evaluated with the available data. We test the new data-driven VMS-ROM in the numerical simulation of four test cases: (i) the 1D Burgers equation with viscosity coefficient $nu = 10^{-3}$; (ii) a 2D flow past a circular cylinder at Reynolds numbers $Re=100$, $Re=500$, and $Re=1000$; (iii) the quasi-geostrophic equations at Reynolds number $Re=450$ and Rossby number $Ro=0.0036$; and (iv) a 2D flow over a backward facing step at Reynolds number $Re=1000$. The numerical results show that the data-driven VMS-ROM is significantly more accurate than standard ROMs. Furthermore, we propose a new hybrid ROM framework for the numerical simulation of fluid flows. This hybrid framework incorporates two closure modeling strategies: (i) A structural closure modeling component that involves the recently proposed data-driven variational multiscale ROM approach, and (ii) A functional closure modeling component that introduces an artificial viscosity term. We also utilize physical constraints for the structural ROM operators in order to add robustness to the hybrid ROM. We perform a numerical investigation of the hybrid ROM for the three-dimensional turbulent channel flow at a Reynolds number $Re = 13,750$. In addition, we focus on the mathematical foundations of ROM closures. First, we extend the verifiability concept from large eddy simulation to the ROM setting. Specifically, we call a ROM closure model verifiable if a small ROM closure model error (i.e., a small difference between the true ROM closure and the modeled ROM closure) implies a small ROM error. Second, we prove that a data-driven ROM closure (i.e., the data-driven variational multiscale ROM) is verifiable. For strategy (II), we propose new Lagrangian inner products that we use together with Eulerian and Lagrangian data to construct new Lagrangian ROMs. We show that the new Lagrangian ROMs are orders of magnitude more accurate than the standard Eulerian ROMs, i.e., ROMs that use standard Eulerian inner product and data to construct the ROM basis. Specifically, for the quasi-geostrophic equations, we show that the new Lagrangian ROMs are more accurate than the standard Eulerian ROMs in approximating not only Lagrangian fields (e.g., the finite time Lyapunov exponent (FTLE)), but also Eulerian fields (e.g., the streamfunction). We emphasize that the new Lagrangian ROMs do not employ any closure modeling to model the effect of discarded modes (which is standard procedure for low-dimensional ROMs of complex nonlinear systems). Thus, the dramatic increase in the new Lagrangian ROMs' accuracy is entirely due to the novel Lagrangian inner products used to build the Lagrangian ROM basis. / Doctor of Philosophy / Reduced order models (ROMs) are popular in physical and engineering applications: for example, ROMs are widely used in aircraft designing as it can greatly reduce computational cost for the aircraft's aeroelastic predictions while retaining good accuracy. However, for high Reynolds number turbulent flows, such as blood flows in arteries, oil transport in pipelines, and ocean currents, the standard ROMs may yield inaccurate results. In this dissertation, to improve ROM's accuracy for turbulent flows, we investigate three different types of ROMs. In this dissertation, both numerical and theoretical results show that the proposed new ROMs yield more accurate results than the standard ROM and thus can be more useful.

Digital Signal Processing has been dominated by the Fourier transform since the Fast Fourier Transform (FFT) was developed in 1965 by Cooley and Tukey. In the 1980's a new transform was developed called the wavelet transform, even though the first wavelet goes back to 1910. With the Fourier transform, all information about localized changes in signal features are spread out across the entire signal space, making local features global in scope. Wavelets are able to retain localized information about the signal by applying a function of a limited duration, also called a wavelet, to the signal. As with the Fourier transform, the discrete wavelet transform has an inverse transform, which allows us to make changes in a signal in the wavelet domain and then transform it back in the time domain. In this thesis, we have investigated the filtering properties of this technique and analyzed its performance under various settings. Another popular application of wavelet transform is data compression, such as described in the JPEG 2000 standard and compressed digital storage of fingerprints developed by the FBI. Previous work on filtering has focused on the discrete wavelet transform. Here, we extended that method to the stationary wavelet transform and found that it gives a performance boost of as much as 9 dB over that of the discrete wavelet transform. We also found that the SNR of noise filtering decreases as a frequency of the base signal increases up to the Nyquist limit for both the discrete and stationary wavelet transforms. Besides filtering the signal, the discrete wavelet transform can also be used to estimate the standard deviation of the white noise present in the signal. We extended the developed estimator for the discrete wavelet transform to the stationary wavelet transform. As with filtering, it is found that the quality of the estimate decreases as the frequency of the base signal increases. Many interesting signals are self-similar, which means that one of their properties is invariant on many different scales. One popular example is strict self-similarity, where an exact copy of a signal is replicated on many scales, but the most common property is statistical self-similarity, where a random segment of a signal is replicated on many different scales. In this work, we investigated wavelet-based methods to detect statistical self-similarities in a signal and their performance on various types of self-similar signals. Specifically, we found that the quality of the estimate depends on the type of the units of the signal being investigated for low Hurst exponent and on the type of edge padding being used for high Hurst exponent. / Master of Science

Exploring the concepts of long range aerial transport of microorganisms is the main motivation of this study. For this purpose we use theories and concepts of dynamical systems in the context of geophysical fluid systems. We apply powerful notions such as finite-time Lyapunov exponent (FTLE) and the associated Lagrangian coherent structures (LCS) and we attempt to provide mathematical explanations and frameworks for some applied questions which are based on realistic concerns of atmospheric transport phenomena. Accordingly, we quantify the accuracy of prediction of FTLE-LCS features and we determine the sensitivity of such predictions to forecasting parameters. In addition, we consider the spatiotemporal resolution of the operational data sets and we propose the concept of probabilistic source and destination regions which leads to the definition of stochastic FTLE fields. Moreover, we put forward the idea of using ensemble forecasting to quantify the uncertainty of the forecast results. Finally, we investigate the statistical properties of localized measurements of atmospheric microbial structure and their connections to the concept of local FTLE time-series. Results of this study would pave the way for more efficient models and management strategies for the spread of infectious diseases affecting plants, domestic animals, and humans. / Ph. D.

Yes / We study transmission over multiple-input multiple-output (MIMO) block-fading channels with imperfect channel state information (CSI) at both the transmitter and receiver. Specifically, based on mismatched decoding theory for a fixed channel realization, we investigate the largest achievable rates with independent and identically distributed inputs and a nearest neighbor decoder. We then study the corresponding information outage probability in the high signal-to-noise ratio (SNR) regime and analyze the interplay between estimation error variances at the transmitter and at the receiver to determine the optimal outage exponent, defined as the high-SNR slope of the outage probability plotted in a logarithmic-logarithmic scale against the SNR. We demonstrate that despite operating with imperfect CSI, power adaptation can offer substantial gains in terms of outage exponent. / A. T. Asyhari was supported in part by the Yousef Jameel Scholarship, University of Cambridge, Cambridge, U.K., and the National Science Council of Taiwan under grant NSC 102-2218-E-009-001. A. Guillén i Fàbregas was supported in part by the European Research Council under ERC grant agreement 259663 and the Spanish Ministry of Economy and Competitiveness under grant TEC2012-38800-C03-03.

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Předkládaná dizertační práce se zabývá stanovením hlavních členů Williamsova asymptotického rozvoje popisujícího rovinné elektro-elastické pole v okolí piezoelektrických bi-materiálových vrubů a trhlin na rozhraní za použití rozšířeného Lechnického-Eshelbyho-Strohova formalismu v návaznosti na čistě anizotropní pružnost. Je ukázáno, že rozšířený Lechnického-Eshelbyho-Strohův formalismus představuje spolu s moderními programovacími koncepty v jazyku Python efektivní a také praktický nástroj pro lomovou analýzu piezoelektrických bi-materiálů. Teoretická část práce popisuje aspekty anizotropní pružnosti a její návaznost na piezoelektrické materiály. Základní rovnice zaměřené na speciální typy monoklinických materiálů, které umožňují oddělení rovinného a anti-rovinného problému, jsou vyjádřeny pomocí komplexních potenciálů. V praktické části práce je sestaven problém vlastního hodnot pro bi-materiálový vrub, na jehož základě jsou stanoveny exponenty singularity a pomocí dvoustavového -integrálu také zobecněné faktory intenzity napětí. Veškeré vztahy a numerické procedury jsou následně rozšířeny na problém piezoelektrických bi-materiálových vrubů a podrobně prozkoumány v uvedených příkladech. Zvláštní pozornost je věnována přechodu asymptotického řešení téměř zavřených vrubů a trhlin na rozhraní. Vliv směru polarizace na asymptotické řešení je také zkoumán. Přesnost stanovení zobecněných faktorů intenzity napětí je testována srovnáním asymptotického řešení a řešení získaného pomocí metody konečných prvků s velmi jemnou sítí konečných prvků. Na závěr je formalismus modifikován pro nepiezoelektrické materiály.

The thesis deals with design, implementation and optimization of a model based on artificial intelligence and neural networks, which is able to predict future time series prices on a stock market. Main goal is to create an object oriented application for successful future trend prediction of financial derivatives with the use of cooperating methods such as Hurst exponent evaluation and automated market simulation.

Presented diploma thesis is concerned with problems of a stress singularity exponent and a generalized stress intensity factor determination, by dint the stress field in the vicinity of the stress concentrator can be consecutively determined. This task is possible to sectionalize into three parts. The first part summarizes basic information about linear anisotropic materials, deals with fundamentals of the linear elastic fracture mechanics and introduces its generalization to the case of the generalized stress intensity factors. The second part is dedicated to a special theory of anisotropic elasticity - Lekhnitskii-Eshelby-Stroh formalism (LES). Furthermore, a theory of the psi-integral is introduced, by dint the stress intensity factor is determined. The final part applies the LES theory and the psi-integral to the concrete material configuration of a crack on the bimaterial interface, a special example of a sharp bimaterial notch. By means of analytical-numerical algorithm in ANSYS and Silverforst FNT95 software the stress singularity exponents and generalised stress intensity factors are consecutively computed.

Die Charakterisierung hochdimensionaler Systeme mit Lyapunov-Instabilität wird durch das Lyapunov-Spektrum und die zugehörigen Lyapunov-Vektoren ermöglicht. Für eine Vielzahl von derartigen Systemen (Coupled-Map-Lattices, Hartkugel-Systeme, Systeme mit ausgedehnten Potentialen ...) konnte durch die Untersuchung der Lyapunov-Vektoren die Existenz von hydrodynamischen Lyapunov-Moden nachgewiesen werden. Diese kollektiven Anregungen zeigen sich in Lyapunov-Vektoren, deren Lyapunov-Exponenten dem Betrage nach am kleinsten sind. Da Lyapunov-Exponenten charakteristische Zeitskalen innerhalb der Systeme repräsentieren, ist durch die Lyapunov-Moden eine Untersuchung des Langzeitverhaltens möglich. In dieser Arbeit werden die hydrodynamischen Lyapunov-Moden durch Molekulardynamiksimulationen von mehrkomponentigen Lennard-Jones-Flüssigkeiten untersucht. Die Charakterisierung der Lyapunov-Moden zeigt im weiteren eine Ähnlichkeit zu Dispersionsrelationen von Phononen.